Integrating Quantitative and Qualitative Approaches to Poverty Measurement

Transcription

1 Integrating Quantitative and Qualitative Approaches to Poverty Measurement Michael Woolcock Development Research Group World Bank January 22, 2002

2 Overview Starting Points Types of Methods and Data Integrating Qualitative and Quantitative Approaches In parallel In series Three Examples 1 Guatemala Poverty Assessment (GUAPA) 2 Delhi slums study 3 St. Lucia social assessment Final Thoughts

3 Starting Points Questions drive methods (not vice versa) assemble highest quality data to answer questions answers may require single, multiple data forms

4 Starting Points Questions drive methods (not vice versa) assemble highest quality data to answer questions answers may require single, multiple data forms Qual/quan disputes often stem from conflating methods and data mismatches between question, methods and data assumptions that different standards apply

5 Starting Points Questions drive methods (not vice versa) assemble highest quality data to answer questions answers may require single, multiple data forms Qual/quan disputes often stem from conflating methods and data mismatches between question, methods and data assumptions that different standards apply Integrating qual and quan approaches In parallel, in series Three contemporary examples

6 Types of Data and Methods Quan Data Qual Quan Qual Methods Adapted from Hentschel, 1999

7 Types of Data and Methods Quan Standard Survey Data Qual Quan Qual Methods Adapted from Hentschel, 1999

8 Types of Data and Methods Quan Subjective Welfare Standard Survey Data Qual Quan Qual Methods Adapted from Hentschel, 1999

9 Types of Data and Methods Quan Subjective Welfare Standard Survey Data Qual Ethnography PRA Quan Qual Methods Adapted from Hentschel, 1999

10 Types of Data and Methods Quan Subjective Welfare Standard Survey Data Qual Ethnography PRA Qual Quan Quantitative Anthropology Small-N Matched Comparisons Methods Adapted from Hentschel, 1999

11 How to integrate Qual and Quan? Quan Subjective Welfare Standard Survey Data Qual Ethnography PRA Qual Quan Quantitative Anthropology Small-N Matched Comparisons Methods Adapted from Hentschel, 1999

12 Integrating Qualitative and Quantitative Approaches Qual/Quan in parallel Quantitative Effects ( How much ) Extrapolation Reliability Large, similar cases

13 Integrating Qualitative and Quantitative Approaches Qual/Quan in parallel Quantitative Effects ( How much ) Extrapolation Reliability Large, similar cases Qualitative Processes ( How ) Unobservables Contexts, histories Quick turn-around Small, dissimilar cases

14 Integrating Qualitative and Quantitative Approaches Qual/Quan in parallel Quantitative Effects ( How much ) Extrapolation Reliability Large, similar cases Qualitative Processes ( How ) Unobservables Contexts, histories Quick turn-around Small, dissimilar cases Qual/Quan in series Iterative exchange, dialogue 1 Context (qual) 2 Design survey (quan) 3 Pre-test survey (qual) 4 Implement survey (quan) 5 Data analysis (quan and qual)

15 Integrating Qualitative and Quantitative Approaches Qual/Quan in parallel Quantitative Effects ( How much ) Extrapolation Reliability Large, similar cases Qualitative Processes ( How ) Unobservables Contexts, histories Quick turn-around Small, dissimilar cases Qual/Quan in series Iterative exchange, dialogue 1 Context (qual) 2 Design survey (quan) 3 Pre-test survey (qual) 4 Implement survey (quan) 5 Data analysis (quan and qual) Missing/weak quan data Generating new data Building on existing data Thinking quan, acting qual Identifying valid instruments

16 Three current examples 1 Poverty in Guatemala In Parallel Quan: expanded LSMS first social capital module large differences by region, gender, income, ethnicity pervasive elite capture

17 Three current examples 1 Poverty in Guatemala In Parallel Quan: expanded LSMS first social capital module large differences by region, gender, income, ethnicity pervasive elite capture Qual: 10 villages (5 different ethnic groups) perceptions of exclusion, access to services fear of reprisal, of children being stolen legacy of shocks (political and natural) links to LSMS data

18 Three current examples 1 Poverty in Guatemala In Parallel Quan: expanded LSMS first social capital module large differences by region, gender, income, ethnicity pervasive elite capture Qual: 10 villages (5 different ethnic groups) perceptions of exclusion, access to services fear of reprisal, of children being stolen legacy of shocks (political and natural) links to LSMS data 2 Poverty in Delhi slums In Series Qual: 4 migrant communities near, far, recent, long-term Quan: 800 randomly selected representative households

19 Three current examples 1 Poverty in Guatemala In Parallel Quan: expanded LSMS first social capital module large differences by region, gender, income, ethnicity pervasive elite capture Qual: 10 villages (5 different ethnic groups) perceptions of exclusion, access to services fear of reprisal, of children being stolen legacy of shocks (political and natural) links to LSMS data 2 Poverty in Delhi slums In Series Qual: 4 migrant communities near, far, recent, long-term Quan: 800 randomly selected representative households From survival to mobility role of norms (sharing, status) and networks (kinship, politics) housing, employment transitions property rights Understanding governance managing collective action crucial role of service provision

20 Three current examples 3 Poverty in St. Lucia In Series Country context very small; old but usable census data goal: 12 poor communities for PPA

21 Three current examples 3 Poverty in St. Lucia In Series Country context very small; old but usable census data goal: 12 poor communities for PPA Quan: use of census, map 459 potential communities use census to identify 200 poorest......and high/low access to water......and close to/far from main road

22 Three current examples 3 Poverty in St. Lucia In Series Country context very small; old but usable census data goal: 12 poor communities for PPA Quan: use of census, map 459 potential communities use census to identify 200 poorest......and high/low access to water......and close to/far from main road Qual: use local staff (20 people) 3-hour selection meeting 4 groups of 5 staff; select 4 communities... by employment variation, geographical proximity, exposure to hurricane

23 Three current examples 3 Poverty in St. Lucia In Series Country context very small; old but usable census data goal: 12 poor communities for PPA Quan: use of census, map 459 potential communities use census to identify 200 poorest......and high/low access to water......and close to/far from main road Qual: use local staff (20 people) 3-hour selection meeting 4 groups of 5 staff; select 4 communities... by employment variation, geographical proximity, exposure to hurricane! RESULT: total buy-in from local staff

24 Final thoughts Mixed methods are... Difficult technically administratively (finding, coordinating staff) no naturally supportive constituency to provide funding moral support detailed professional critique

25 Final thoughts Mixed methods are... Difficult technically administratively (finding, coordinating staff) no naturally supportive constituency to provide funding moral support detailed professional critique Time consuming

26 Final thoughts Mixed methods are... Difficult technically administratively (finding, coordinating staff) no naturally supportive constituency to provide funding moral support detailed professional critique Time consuming Enormously rewarding! more, better data -> better policy bridging disciplines, sectors development as bio-technology (multiple agents and agencies of expertise) not math (lone genius) problem

27 Reading suggestions Bamberger, Michael (ed.) (2000) Integrating Qualitative and Quantitative Research in Development Projects (Washington, DC: The World Bank) Hentschel, Jesko (1999) Contextuality and Data Collection Methods: A Framework and Application to Health Service Utilisation Journal of Development Studies 35(4): Rao, Vijayendra (2001) Poverty and public celebrations in rural India Annals of the American Academy of Political and Social Science 573: Rao, Vijayendra, Saumitra Jha, and Michael Woolcock (2002) Survival and Mobility Strategies in Delhi Slums: A Mixed Methods Analysis Mimeo, The World Bank, forthcoming Woolcock, Michael (2001) Social Assessments and Program Evaluation with Limited Formal Data: Thinking Quantitatively, Acting Qualitatively Social Development Briefing Note No. 68, The World Bank World Bank (2002) Guatemala Poverty Assessment Washington, DC: The World Bank, forthcoming [Kathy Lindert, Task Manager]